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Reality checks and nested forecast model comparisons

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  • Todd E. Clark
  • Michael W. McCracken

Abstract

This paper develops a novel and effective bootstrap method for simulating asymptotic critical values for tests of equal forecast accuracy and encompassing among many nested models. The bootstrap, which combines elements of fixed regressor and wild bootstrap methods, is simple to use. We first derive the asymptotic distributions of tests of equal forecast accuracy and encompassing applied to forecasts from multiple models that nest the benchmark model – that is, reality check tests applied to nested models. We then prove the validity of the bootstrap for these tests. Monte Carlo experiments indicate that our proposed bootstrap has better finite-sample size and power than other methods designed for comparison of non-nested models. We conclude with empirical applications to multiple-model forecasts of commodity prices and GDP growth.

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Bibliographic Info

Paper provided by Federal Reserve Bank of St. Louis in its series Working Papers with number 2010-032.

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Date of creation: 2010
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Handle: RePEc:fip:fedlwp:2010-032

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Keywords: Economic forecasting;

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  1. Rapach, David E. & Wohar, Mark E., 2006. "In-sample vs. out-of-sample tests of stock return predictability in the context of data mining," Journal of Empirical Finance, Elsevier, vol. 13(2), pages 231-247, March.
  2. Kilian, Lutz & Taylor, Mark P., 2003. "Why is it so difficult to beat the random walk forecast of exchange rates?," Journal of International Economics, Elsevier, vol. 60(1), pages 85-107, May.
  3. Sarno, Lucio & Thornton, Daniel L & Valente, Giorgio, 2004. "Federal Funds Rate Prediction," CEPR Discussion Papers 4587, C.E.P.R. Discussion Papers.
  4. Yu-chin Chen & Kenneth Rogoff & Barbara Rossi, 2008. "Can Exchange Rates Forecast Commodity Prices?," Working Papers UWEC-2008-11-FC, University of Washington, Department of Economics, revised Oct 2009.
  5. Amit Goyal & Ivo Welch, 2004. "A Comprehensive Look at the Empirical Performance of Equity Premium Prediction," Yale School of Management Working Papers amz2412, Yale School of Management, revised 01 Jan 2006.
  6. Sílvia Gonçalves & Lutz Kilian, 2003. "Bootstrapping Autoregressions with Conditional Heteroskedasticity of Unknown Form," CIRANO Working Papers 2003s-17, CIRANO.
  7. Cheung, Yin-Wong & Chinn, Menzie & Garcia Pascual, Antonio, 2003. "Empirical Exchange Rate Models of the Nineties: Are Any Fit to Survive?," Santa Cruz Department of Economics, Working Paper Series qt5fc508pt, Department of Economics, UC Santa Cruz.
  8. Hubrich, Kirstin, 2003. "Forecasting euro area inflation: Does aggregating forecasts by HICP component improve forecast accuracy?," Working Paper Series 0247, European Central Bank.
  9. Denton, Frank T, 1985. "Data Mining as an Industry," The Review of Economics and Statistics, MIT Press, vol. 67(1), pages 124-27, February.
  10. Andreas Billmeier, 2004. "Ghostbusting," IMF Working Papers 04/146, International Monetary Fund.
  11. Alexander W. Butler & Gustavo Grullon & James P. Weston, 2005. "Can Managers Forecast Aggregate Market Returns?," Journal of Finance, American Finance Association, vol. 60(2), pages 963-986, 04.
  12. Todd E. Clark & Michael W. McCracken, 2009. "Nested forecast model comparisons: a new approach to testing equal accuracy," Research Working Paper RWP 09-11, Federal Reserve Bank of Kansas City.
  13. Moench, Emanuel, 2008. "Forecasting the yield curve in a data-rich environment: A no-arbitrage factor-augmented VAR approach," Journal of Econometrics, Elsevier, vol. 146(1), pages 26-43, September.
  14. Clark, Todd E. & West, Kenneth D., 2007. "Approximately normal tests for equal predictive accuracy in nested models," Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
  15. Inoue, Atsushi & Kilian, Lutz, 2002. "In-sample or out-of-sample tests of predictability: which one should we use?," Working Paper Series 0195, European Central Bank.
  16. Amit Goyal & Ivo Welch, 2003. "Predicting the Equity Premium with Dividend Ratios," Management Science, INFORMS, vol. 49(5), pages 639-654, May.
  17. Todd E. Clark & Michael W. McCracken, 1999. "Tests of equal forecast accuracy and encompassing for nested models," Research Working Paper 99-11, Federal Reserve Bank of Kansas City.
  18. Kevin Hoover & Stephen J. Perez, 2003. "Data Mining Reconsidered: Encompassing And The General-To-Specific Approach To Specification Search," Working Papers 9727, University of California, Davis, Department of Economics.
  19. Kirstin Hubrich & Kenneth D. West, 2008. "Forecast Evaluation of Small Nested Model Sets," NBER Working Papers 14601, National Bureau of Economic Research, Inc.
  20. Jan J. J. Groen, 1999. "Long horizon predictability of exchange rates: Is it for real?," Empirical Economics, Springer, vol. 24(3), pages 451-469.
  21. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-44, January.
  22. Hansen, Bruce E., 1992. "Convergence to Stochastic Integrals for Dependent Heterogeneous Processes," Econometric Theory, Cambridge University Press, vol. 8(04), pages 489-500, December.
  23. Hendry, David F. & Hubrich, Kirstin, 2010. "Combining disaggregate forecasts or combining disaggregate information to forecast an aggregate," Working Paper Series 1155, European Central Bank.
  24. Todd Clark & Michael McCracken, 2005. "Evaluating Direct Multistep Forecasts," Econometric Reviews, Taylor & Francis Journals, vol. 24(4), pages 369-404.
  25. McCracken, Michael W., 2007. "Asymptotics for out of sample tests of Granger causality," Journal of Econometrics, Elsevier, vol. 140(2), pages 719-752, October.
  26. Kilian, Lutz, 1999. "Exchange Rates and Monetary Fundamentals: What Do We Learn from Long-Horizon Regressions?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(5), pages 491-510, Sept.-Oct.
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Cited by:
  1. Hubrich, Kirstin & West, Kenneth D., 2009. "Forecast evaluation of small nested model sets," Working Paper Series 1030, European Central Bank.
  2. Inoue, Atsushi & Rossi, Barbara, 2011. "Out-of-Sample Forecast Tests Robust to the Choice of Window Size," CEPR Discussion Papers 8542, C.E.P.R. Discussion Papers.
  3. Christopher J. Neely & David E. Rapach & Jun Tu & Guofu Zhou, 2011. "Forecasting the Equity Risk Premium: The Role of Technical Indicators," Working Papers CoFie-02-2011, Sim Kee Boon Institute for Financial Economics.

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